Computer Science – Learning
Scientific paper
Oct 2010
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010aps..nws.h2006s&link_type=abstract
American Physical Society, 12th Annual Meeting of the Northwest Section of the APS, October 1-2, 2010, abstract #H2.006
Computer Science
Learning
Scientific paper
We have written a software suite designed to facilitate solar data analysis by scientists, students, and the public, anticipating enormous datasets from future instruments. Our ``STAR'' suite includes an interactive learning section explaining 15 classes of solar events, with over 200 images and 18 movies showing examples. Users learn software tools that exploit humans' superior ability (over computers) to identify many events. Upon completion of our tutorial, users are presented with media of various solar events and asked to identify and annotate the images, to test their mastery of the system. Previously, solar physicists manually annotated these features, but with the increasing influx of data it is unrealistic to expect specialized researchers to examine every image that computers cannot fully process. A new approach is needed to efficiently process these data. Providing analysis tools and data access to students and the public have proven efficient in similar astrophysical projects (e.g. the ``Galaxy Zoo''). Goals of the project include public input into the data analysis of very large datasets from future solar satellites, and increased public interest and knowledge about the Sun.
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